A review of multi-criteria decision-making methods for bioenergy systems

被引：140

作者：

Scott, James A. ^{[1
]}

Ho, William ^{[1
]}

Dey, Prasanta K. ^{[1
]}

机构：

[1] Aston Univ, Aston Business Sch, Operat & Informat Management Grp, Birmingham B4 7ET, W Midlands, England

来源：

ENERGY | 2012年 / 42卷 / 01期

关键词：

Bioenergy; Multi-criteria; Multi-attribute; Decision making; RENEWABLE ENERGY; SUPPLY CHAIN; SUSTAINABILITY ASSESSMENT; OPTIMIZATION MODEL; LOGISTICS ISSUES; POWER-GENERATION; BIOMASS; SCENARIOS; TECHNOLOGIES; POLICY;

D O I：

10.1016/j.energy.2012.03.074

中图分类号：

O414.1 [热力学];

学科分类号：

摘要：

Bioenergy schemes are multi-faceted and complex by nature, with many available raw material supplies and technical options and a diverse set of stakeholders holding a raft of conflicting opinions. To develop and operate a successful scheme there are many requirements that should be considered and satisfied. This paper provides a review of those academic works attempting to deal with problems arising within the bioenergy sector using multi-criteria decision-making (MCDM) methods. These methods are particularly suitable to bioenergy given its multi-faceted nature but could be equally relevant to other energy conversion technologies. Related articles appearing in the international journals from 2000 to 2010 are gathered and analysed so that the following two questions can be answered. (i) Which methods are the most popular? (ii) Which problems attract the most attention? The review finds that optimisation methods are most popular with methods choosing between few alternatives being used in 44% of reviewed papers and methods choosing between many alternatives being used in 28%. The most popular application area was to technology selection with 27% of reviewed papers followed by policy decisions with 18%. (C) 2012 Elsevier Ltd. All rights reserved.

引用

页码：146 / 156

页数：11

共 81 条

[1] Sustainability assessment of a hybrid energy system [J].

Afgan, Nain H. ;

Carvalho, Maria G. .

ENERGY POLICY, 2008, 36 (08) :2903-2910

[2]

Afgan NH, 2003, FUEL EN ABSTR, V44, P102

[3] A multi-objective robust optimization model for multi-product multi-site aggregate production planning in a supply chain under uncertainty [J].

Al-e-hashem, S. M. J. Mirzapour ;

Malekly, H. ;

Aryanezhad, M. B. .

INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS, 2011, 134 (01) :28-42

[4] The Tyndall decarbonisation scenarios-Part II: Scenarios for a 60% CO2 reduction in the UK [J].

Anderson, Kevin L. ;

Mander, Sarah L. ;

Bows, Alice ;

Shackley, Simon ;

Agnolucci, Paolo ;

Ekins, Paul .

ENERGY POLICY, 2008, 36 (10) :3764-3773

[5]

[Anonymous], 2001, REFOCUS, P34

[6] How to build multifunctional agricultural landscapes in the US Corn Belt: Add perennials and partnerships [J].

Atwell, Ryan C. ;

Schulte, Lisa A. ;

Westphal, Lynne M. .

LAND USE POLICY, 2010, 27 (04) :1082-1090

[7] Evolutionary algorithms approach for integrated bioenergy supply chains optimization [J].

Ayoub, Nasser ;

Elmoshi, Elsayed ;

Seki, Hiroya ;

Naka, Yuji .

ENERGY CONVERSION AND MANAGEMENT, 2009, 50 (12) :2944-2955

[8] Optimization methods applied to renewable and sustainable energy: A review [J].

Banos, R. ;

Manzano-Agugliaro, F. ;

Montoya, F. G. ;

Gil, C. ;

Alcayde, A. ;

Gomez, J. .

RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2011, 15 (04) :1753-1766

[9] Comparing transport emissions and impacts for energy recovery from domestic waste (EfW): Centralised and distributed disposal options for two UK Counties [J].

Bastin, Lucy ;

Longden, David M. .

COMPUTERS ENVIRONMENT AND URBAN SYSTEMS, 2009, 33 (06) :492-503

[10] Decision-making in energy planning. Application of the Electre method at regional level for the diffusion of renewable energy technology [J].

Beccali, M ;

Cellura, M ;

Mistretta, M .

RENEWABLE ENERGY, 2003, 28 (13) :2063-2087

← 1 2 3 4 5 6 7 8 9 →